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Amazon FBA Profit Calculator

Calculate true FBA profit per unit after referral fees, fulfillment fees, COGS, PPC, and shipping. Know your real margin before you sell.

Trusted by 7-figure Amazon sellers to validate products and protect margins.

Product & Fees

Enter per-unit figures from Seller Central

Your listing price

$

Cost of goods per unit

$

Amazon commission (default 15%)

%

Per-unit FBA fee

$

Optional Costs

Add for a more accurate net profit

Per-unit ad attribution

$

Shipping to FBA per unit

$

Monthly storage per unit

$

Scale to total inventory

Common Referral Fees
Beauty & Health8%
Clothing & Accessories17%
Electronics8%
Home & Garden15%
Toys & Games15%
Sports & Outdoors15%
Grocery & Food8%

Enter Sale Price + COGS

Your FBA profit breakdown will appear here instantly.

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How to Calculate Amazon FBA Profit

What costs does Amazon FBA take?

Every FBA sale incurs: Referral Fee (8–20% depending on category), FBA Fulfillment Fee (based on size/weight), and optionally Monthly Storage Fees. You also need to factor in your COGS, inbound shipping costs, and PPC ad spend to see true net profit.

What is a good FBA profit margin?

Most successful FBA sellers target 20–40% net margin after all costs. Below 15% is risky — any fee change, price war, or ad cost increase can wipe out profits. Above 40% is excellent and scalable.

What is ROI on COGS?

ROI on COGS = (Net Profit ÷ COGS) × 100. Serious FBA sellers target 50–150% ROI. A 100% ROI means every $1 in product cost returns $1 in profit. This helps you compare sourcing opportunities and allocate capital to the best-performing SKUs.

Break-even price calculation

Break-even price = Total costs ÷ (1 − referral fee %). This is the absolute minimum you must charge to break even. Any price below this means a guaranteed loss per unit. Always keep your actual price at least 20% above break-even for a healthy buffer.

Built by MishraBrandTechAi — we build FBA analytics systems, Sellerboard P&L dashboards, and inventory intelligence for 7-figure Amazon brands. See our analytics work →